FastDeploy/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "fastdeploy/pybind/main.h"

namespace fastdeploy {
void BindPPDet(pybind11::module& m) {
  pybind11::class_<vision::detection::PaddleDetPreprocessor>(
      m, "PaddleDetPreprocessor")
      .def(pybind11::init<std::string>())
      .def("run", [](vision::detection::PaddleDetPreprocessor& self, std::vector<pybind11::array>& im_list) {
        std::vector<vision::FDMat> images;
        for (size_t i = 0; i < im_list.size(); ++i) {
          images.push_back(vision::WrapMat(PyArrayToCvMat(im_list[i])));
        }
        std::vector<FDTensor> outputs;
        if (!self.Run(&images, &outputs)) {
          throw std::runtime_error("Failed to preprocess the input data in PaddleDetPreprocessor.");
        }
        for (size_t i = 0; i < outputs.size(); ++i) {
          outputs[i].StopSharing();
        }
        return outputs;
      });

  pybind11::class_<vision::detection::PaddleDetPostprocessor>(
      m, "PaddleDetPostprocessor")
      .def(pybind11::init<>())
      .def("run", [](vision::detection::PaddleDetPostprocessor& self, std::vector<FDTensor>& inputs) {
        std::vector<vision::DetectionResult> results;
        if (!self.Run(inputs, &results)) {
          throw std::runtime_error("Failed to postprocess the runtime result in PaddleDetPostprocessor.");
        }
        return results;
      })
      .def("apply_decode_and_nms",
           [](vision::detection::PaddleDetPostprocessor& self){
             self.ApplyDecodeAndNMS();
           })
      .def("run", [](vision::detection::PaddleDetPostprocessor& self, std::vector<pybind11::array>& input_array) {
        std::vector<vision::DetectionResult> results;
        std::vector<FDTensor> inputs;
        PyArrayToTensorList(input_array, &inputs, /*share_buffer=*/true);
        if (!self.Run(inputs, &results)) {
          throw std::runtime_error("Failed to postprocess the runtime result in PaddleDetPostprocessor.");
        }
        return results;
      });

  pybind11::class_<vision::detection::PPDetBase, FastDeployModel>(m, "PPDetBase")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>())
      .def("predict",
           [](vision::detection::PPDetBase& self, pybind11::array& data) {
             auto mat = PyArrayToCvMat(data);
             vision::DetectionResult res;
             self.Predict(&mat, &res);
             return res;
           })
      .def("batch_predict",
           [](vision::detection::PPDetBase& self, std::vector<pybind11::array>& data) {
             std::vector<cv::Mat> images;
             for (size_t i = 0; i < data.size(); ++i) {
              images.push_back(PyArrayToCvMat(data[i]));
             }
             std::vector<vision::DetectionResult> results;
             self.BatchPredict(images, &results);
             return results;
           })
      .def_property_readonly("preprocessor", &vision::detection::PPDetBase::GetPreprocessor)
      .def_property_readonly("postprocessor", &vision::detection::PPDetBase::GetPostprocessor);


  pybind11::class_<vision::detection::PPYOLO, vision::detection::PPDetBase>(m, "PPYOLO")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::PPYOLOE, vision::detection::PPDetBase>(m, "PPYOLOE")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::PicoDet, vision::detection::PPDetBase>(m, "PicoDet")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::PaddleYOLOX, vision::detection::PPDetBase>(m, "PaddleYOLOX")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::FasterRCNN, vision::detection::PPDetBase>(m, "FasterRCNN")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::YOLOv3, vision::detection::PPDetBase>(m, "YOLOv3")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::MaskRCNN, vision::detection::PPDetBase>(m, "MaskRCNN")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());

  pybind11::class_<vision::detection::SSD, vision::detection::PPDetBase>(m, "SSD")
      .def(pybind11::init<std::string, std::string, std::string, RuntimeOption,
                          ModelFormat>());
}
}  // namespace fastdeploy